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arXiv Machine Learning By Arslan Bisharat, Oudom Hean

Evaluating Financial Sentiment in the Age of AI

Read the original on arXiv Machine Learning →

The paper evaluates twelve financial sentiment models—including dictionary-based methods, finance-specific transformers, and open-source large language models—using linguistic and economic validity criteria. General-purpose LLMs match finance-specific transformers in classification performance but do not yield stronger economic relationships. While several models correlate with earnings surprises, none shows a significant link to next‑day stock returns, and performance is strongest for large earnings beats or misses.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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